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Abstract:

This disclosure provides a method and a device for estimating a quality
factor based on zero offset VSP (Vertical Seismic Profiling) data,
wherein the method includes the following steps: determining a
transmission coefficient between two adjacent VSP channels based on an
interval velocity of a seismic wave in the zero offset VSP data; and
determining the transmission coefficient as an indeterminate coefficient
in an objective function of an index method, and estimating the quality
factor according to the objective function of the index method.

Claims:

1. A method for estimating a quality factor based on zero offset Vertical
Seismic Profiling (VSP) data, comprising: determining a transmission
coefficient between two adjacent VSP channels based on an interval
velocity of a seismic wave in the zero offset VSP data; and determining
the transmission coefficient as an indeterminate coefficient in an
objective function of an index method, and estimating the quality factor
according to the objective function of the index method.

2. The method according to claim 1, wherein the step of determining the
transmission coefficient between the two adjacent VSP channels based on
the interval velocity of the seismic wave in the zero offset VSP data,
comprises: determining the transmission coefficient in accordance with a
following formula: P k = 1 + v k - v k - 1 v k + v k -
1 ##EQU00010## where Pk represents the transmission
coefficient, vk represents an interval velocity between (k-1)th
and kth VSP channels, and vk-1 represents an interval velocity
between (k-2)th and (k-1)th VSP channels.

3. The method according to claim 1, wherein the step of determining the
transmission coefficient as the indeterminate coefficient in the
objective function of the index method, and estimating the quality factor
according to the objective function of the index method, comprises:
determining a value range of the quality factor; acquiring, by way of
scanning the quality factor within the value range, the quality factor
which allows the objective function to have a minimum matching error; and
taking the quality factor corresponding to the objective function with
the minimum matching error as an estimated quality factor.

5. The method according to claim 1, wherein the step of determining the
transmission coefficient between the two adjacent VSP channels based on
the interval velocity of the seismic wave in the zero offset VSP data,
comprises: performing a geometric diffusion compensation and a wave field
separation for the zero offset VSP data to obtain a down-going wave
field; and determining the transmission coefficient between the two
adjacent VSP channels, according to the interval velocity of the seismic
wave in the down-going wave field.

6. A device for estimating a quality factor based on zero offset Vertical
Seismic Profiling (VSP) data comprising a processor configured to:
determine a transmission coefficient between two adjacent VSP channels
based on an interval velocity of a seismic wave in the zero offset VSP
data; and determine the transmission coefficient as an indeterminate
coefficient in an objective function of an index method, and estimate the
quality factor according to the objective function of the index method.

8. The device according to claim 6, wherein the processor is further
configured to determine a transmission coefficient between two adjacent
VSP channels by: determining a value range of the quality factor;
acquiring, by way of scanning the quality factor within the value range,
the quality factor which allows the objective function to have a minimum
matching error; and taking the quality factor corresponding to the
objective function with the minimum matching error as an estimated
quality factor.

10. The device according to claim 6, wherein the processor is further
configured to determine a transmission coefficient between two adjacent
VSP channels by: performing a geometric diffusion compensation and a wave
field separation for the zero offset VSP data to obtain a down-going wave
field; and determining the transmission coefficient between the two
adjacent VSP channels according to the interval velocity of the seismic
wave in the down-going wave field.

Description:

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application is a continuation of International Application No.
PCT/CN2013/090914 filed on Dec. 30, 2013, which is hereby incorporated by
reference in its entirety.

TECHNICAL FIELD

[0002] This disclosure relates to the technical field of physical
exploration, and more particularly, to a method and a device for
estimating a quality factor based on zero offset VSP (Vertical Seismic
Profiling) data.

BACKGROUND

[0003] When the seismic waves propagate in the earth medium, absorption
caused by medium viscosity can cause energy attenuation and velocity
dispersion for seismic waves since the earth medium is not perfectly
elastic. Such attenuation characteristics inherent in a medium are
generally described by a quality factor Q. Due to the existence of the
quality factor, attenuation of high-frequency energy for seismic wave is
stronger than that of the low-frequency energy, and propagation velocity
of high-frequency components is faster than that of low-frequency
components, and meanwhile it may further cause energy weaker and
frequency band narrower in the seismic profile deep-layer, thereby
resulting in a lower resolution of data and increasing the difficulty of
fine interpretation of seismic data.

[0004] With respect to the above problem, an inverse Q filtering is an
effective means for compensating for absorption attenuation of the
seismic data, which can compensate and correct energy attenuation and
velocity dispersion during the seismic wave propagation, thereby
improving data resolution.

[0005] An accurate estimation of quality factors is the premise of
performing the inverse Q filtering, as compared to surface seismic data,
vertical seismic profiling (VSP) data is widely applied to quality factor
estimation since it is subjected to less interference. After a comparison
study was previously conducted for a time domain method (such as an
amplitude attenuation method, a rise time method, a wavelet simulation
method, an analytic signal method and the like) and a frequency domain
method (such as a matching method, a spectrum simulation method, a
spectral ratio method and the like), using the VSP data, it is found that
there is no method that applies to any situation, and it depends on the
quality of the data that how well the effect produced by each method is.
Currently, there is a centroid frequency shift method, which mainly
utilizes a change in centroid frequency during seismic wave propagation
to obtain a quality factor. In the abovementioned methods, the spectral
ratio method is a common method for estimating the quality factor, and
the quality factor is estimated by utilizing a linear relation between
the spectrum ratio logarithm and the frequency, however, the slope
fitting thereof is easily affected by the spectrum ratio logarithm error,
which leads to the stability of estimating the quality factor being
affected. The index method effectively avoids drawbacks caused by
existence of the spectrum ratio logarithm, and the index method estimates
the quality factor by using a forward matching approach, and is capable
of effectively improving the stability of estimating the quality factor.
However, it is found in the practical operation that relatively large
errors may often occur on the quality factor estimated by the index
method, and the accuracy of estimating the quality factor is difficult to
be guaranteed.

SUMMARY

[0006] The embodiments of the present invention provide a method for
estimating a quality factor based on zero offset VSP data, including:

[0007] determining a transmission coefficient between two adjacent VSP
channels based on an interval velocity of a seismic wave in the zero
offset VSP data; and

[0008] determining the transmission coefficient as an indeterminate
coefficient in an index method objective function, and estimating the
quality factor according to the objective function of the index method.

[0009] The embodiments of the present invention provide a device for
estimating a quality factor based on zero offset VSP (Vertical Seismic
Profiling) data, comprising a processor configured to:

[0010] determine a transmission coefficient between two adjacent VSP
channels based on an interval velocity of a seismic wave in the zero
offset VSP data; and

[0011] determine the transmission coefficient as an indeterminate
coefficient in an objective function of an index method, and estimate the
quality factor according to the objective function of the index method.

BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The accompanying drawings described herein are used to provide a
further understanding of the present invention and constitute a part of
this application, but are not construed as limitations to the present
invention. In the drawings:

[0013] FIG. 1 is a flow diagram of a method of estimating a quality factor
based on zero offset VSP data according to an embodiment of the present
invention;

[0014] FIG. 2 is a structural block diagram of a device of estimating a
quality factor based on the zero offset VSP data according to an
embodiment of the present invention;

[0015] FIG. 3 is a schematic diagram of a zero offset displacement VSP
observing system according to an embodiment of the present invention;

[0016] FIG. 4 is a schematic diagram of attenuation VSP direct wave first
arrival record according to an embodiment of the present invention;

[0017] FIG. 5 is a schematic diagram of a result of estimating a quality
factor by a noise-free data index method according to an embodiment of
the present invention;

[0018] FIG. 6 is a schematic diagram of a result of estimating a quality
factor by a noise data index method according to an embodiment of the
present invention;

[0019] FIG. 7 is a schematic diagram of matching errors of the index
method corresponding to different quality factors for the noise-free data
according to an embodiment of the present invention;

[0020] FIG. 8 is a schematic diagram of a coefficient Ck of the index
method corresponding to different quality factors for the noise-free data
according to an embodiment of the present invention;

[0021] FIG. 9 is a schematic diagram of matching errors of the index
method corresponding to different quality factors for the noise data
according to an embodiment of the present invention;

[0022] FIG. 10 is a schematic diagram of a coefficient Ck of the
index method corresponding to different quality factors for the
noise-free data according to an embodiment of the present invention;

[0023] FIG. 11 is a schematic diagram of a result of estimating the
quality factor by the index method in the case where a coefficient
Ck=1 is set according to an embodiment of the present invention;

[0024] FIG. 12 is a schematic diagram of a stability analysis of the index
method when the coefficient Ck for the noise-free data is known
according to an embodiment of the present invention;

[0025] FIG. 13 is a schematic diagram of a stability analysis of the index
method when the coefficient Ck for the noise data is known according
to an embodiment of the present invention;

[0026] FIG. 14 is a schematic diagram of a velocity model and a quality
factor model according to an embodiment of the present invention;

[0027] FIG. 15 is a schematic diagram of a result of estimating the
quality factor by the spectral ratio method, the index method and the
improved index method for the noise-free data according to an embodiment
of the present invention;

[0028] FIG. 16 is a schematic diagram of a result of estimating the
quality factor by the spectral ratio method for the noise data according
to an embodiment of the present invention;

[0029] FIG. 17 is a schematic diagram of a result of estimating the
quality factor by the index method for the noise data according to an
embodiment of the present invention;

[0030] FIG. 18 is a schematic diagram of a result of estimating the
quality factor by the improved index method for the noise data according
to an embodiment of the present invention.

DETAILED DESCRIPTION

[0031] The inventors have found, after conducting a study on the index
method, that the reason that a deviation of accuracy of the quality
factor estimated by the index method occurs is that there exists an
indeterminate coefficient in the index method and the presence of the
indeterminate coefficient affects exertion of the performance of the
index method. Accordingly, the inventors have found, after the study,
that the indeterminate coefficient in the index method can be firstly
obtained, and then the quality factor is estimated, thereby eliminating
the effects of the indeterminate coefficient on the stability and
accuracy of the method, and the stability of estimating the quality
factor can be further improved in such a manner in which the quality
factor is estimated.

[0032] In the embodiment of the present invention, a method for estimating
a quality factor based on zero offset VSP data, as shown in FIG. 1, is
set forth, and the method includes the following steps of:

[0033] Step 101: determining a transmission coefficient between two
adjacent VSP channels based on an interval velocity of a seismic wave in
VSP data;

[0034] Step 102: determining the transmission coefficient as an
indeterminate coefficient in an objective function of an index method,
and estimating the quality factor according to the objective function of
the index method.

[0035] In the above embodiment, the transmission coefficient between the
two VSP channels is determined by the interval velocity of the seismic
wave, and then the transmission coefficient is determined as an
indeterminate coefficient in the objective function of the index method,
and the quality factor is estimated according to the objective function
of the index method, thereby solving the technical problem of lower
stability and accuracy of estimating the quality factor due to the
existence of the indeterminate coefficient in the process of estimating
the quality factor by adopting the index method in the prior art, and
achieving the technical effect of improving stability and accuracy of
estimating the quality factor.

[0036] Specifically, the determination of the transmission coefficient in
the above step 101 can be implemented by the following formula:

P k = 1 + v k - v k - 1 v k + v k - 1 ##EQU00001##

[0037] Where Pk represents the transmission coefficient, vk
represents an interval velocity between (k-1)th and kth VSP
channels, and vk-1 represents an interval velocity between
(k-2)th and (k-1)th VSP channels.

[0038] The reason why the transmission coefficient is taken as the
indeterminate coefficient in the index method is mainly that: the
indeterminate coefficient Ck generally includes two aspects:
geometric diffusion effect Gk during propagation and transmission
loss Pk at a wave impedance interface. In which, an amplitude
attenuation caused by the geometric diffusion effect can be compensated
through a geometric diffusion correction, and thus the problem of
obtaining the coefficient Ck is converted into how to solve the
transmission loss Pk caused by the wave impedance interface.

[0039] After obtaining the transmission coefficient, the transmission
coefficient can be substituted into the objective function of the index
method to obtain the quality factor, that is, substituting the
transmission coefficient as the indeterminate coefficient of the
objective function into the objective function; acquiring, by way of
scanning the quality factor, the quality factor, which allows the
objective function to have a minimum matching error; and taking the
quality factor corresponding to the objective function with the minimum
matching error as the obtained quality factor.

[0041] Where f1 represents a lower frequency limit of a predominant
frequency band, f2 represents an upper frequency limit of the
predominant frequency band, Sk(f) represents an amplitude spectrum
of a seismic wave of kth VSP channel, Sk-1(f) represents an
amplitude spectrum of a seismic wave of (k-1)th VSP channel, tk
represents a propagation time of a seismic wave between kth and
(k-1)th VSP channels, Ck represents the indeterminate
coefficient, Qk represents the quality factor between (k-1)th
and kth VSP channels, and G represents a matching error.

[0042] In each of the abovementioned embodiments, in the step 101 as
mentioned above, the step of determining a transmission coefficient
between two adjacent VSP channels based on the interval velocity of the
seismic wave in the zero offset VSP data, includes: performing a
geometric diffusion compensation and a wave field separation for the zero
offset VSP data to obtain a down-going wave field; and determining the
transmission coefficient between the two adjacent VSP channels according
to the interval velocity of the seismic wave in the down-going wave
field. That is, the data input of the method for estimating a quality
factor based on the zero offset VSP data is the down-going wave field of
the zero offset VSP data that is subjected to the geometric diffusion
compensation.

[0043] Based on the same inventive concept, the embodiment of the present
invention further provides a device for estimating a quality factor based
on zero offset VSP data, as described in the embodiment below. Since the
principle that the device for estimating a quality factor based on zero
offset VSP data solves the problem is similar to the method for
estimating a quality factor based on zero offset VSP data, an
implementation of the device for estimating the quality factor based on
the zero offset VSP data may refer to that of the method for estimating
the quality factor based on the zero offset VSP data, and thus
repetitious descriptions will be omitted. The term "unit" or "module" as
used below can be a combination of software and/or hardware that
implements prescribed functions. Although the device described in the
following embodiments is preferably implemented in software, an
implementation thereof in hardware, or a combination of software and
hardware is also possible and conceived. FIG. 2 is a structural block
diagram of a device of estimating a quality factor based on the zero
offset VSP data according to an embodiment of the present invention. As
shown in FIG. 2, the device includes: a determining module 201 and an
estimating module 202, the structure will be described below. The
determining module 201 is configured to determine a transmission
coefficient between two adjacent VSP channels based on the interval
velocity of the seismic wave in the zero offset VSP data.

[0044] The estimating module 202 is configured to determine the
transmission coefficient as an indeterminate coefficient in an objective
function of an index method, and estimate the quality factor according to
the objective function of the index method.

[0045] In one embodiment, the determining module 201 is specifically
configured to determine the transmission coefficient according to the
following formula:

P k = 1 + v k - v k - 1 v k + v k - 1 ##EQU00003##

[0046] Where Pk represents the transmission coefficient, vk
represents an interval velocity between (k-1)th and kth VSP
channels, and vk-1 represents an interval velocity between
(k-2)th and (k-1)th VSP channels.

[0047] In one embodiment, the estimating module 202 includes:

[0048] a determining unit configured to determine a value range of the
quality factor;

[0049] a scanning unit configured to acquire, by way of scanning the
quality factor within the value range, the quality factor which allows
the objective function to have the minimum matching error; and

[0050] an estimating unit configured to take the quality factor
corresponding to the objective function with the minimum matching error
as an estimated quality factor.

[0052] Where f1 represents a lower frequency limit of a predominant
frequency band, f2 represents an upper frequency limit of a
predominant frequency band, Sk(f) represents an amplitude spectrum
of a seismic wave of kth VSP channel, Sk-1(f) represents an
amplitude spectrum of a seismic wave of (k-1)th VSP channel, tk
represents a propagation time of a seismic wave between kth and
(k-1)th VSP channels, Ck represents the indeterminate
coefficient, Qk represents the quality factor between (k-1)th
and kth VSP channels, and G represents a matching error.

[0053] In one embodiment, the determining module 201 includes: a wave
field separation unit configured to perform a geometric diffusion
compensation and a wave field separation for the zero offset VSP data to
obtain a down-going wave field; and a transmission coefficient
determining unit configured to determine the transmission coefficient
between the two adjacent VSP channels according to the interval velocity
of the seismic wave in the down-going wave field.

[0054] The present invention further provides a specific embodiment for a
detailed description of the above method for estimating a quality factor
based on zero offset VSP data. However, it is noted that the specific
embodiment is provided merely for a better illustration of the present
invention, but is not to be construed as improper limitations to the
present invention.

[0055] Considering the Earth's absorption and attenuation effect, the
amplitude spectrum of the seismic wavelets during propagation can be
expressed as:

[0056] Where f1 represents a frequency, and Sk(f) and
Sk-1(f) respectively represents an amplitude spectrum of seismic
waves where depth of detection points as shown in FIG. 3 is zk and
zk-1, tkrepresents a propagation time of the seismic waves
between two detection points zk and zk-1, the coefficient
Ck represents a number independent of the frequency, Qk
represents an interlayer quality factor, it is generally assumed that it
does not depend on the frequency. It is noted that the k herein
represents the detection point number in the process of collecting data,
and represents a channel number of VSP channels in the process of
calculating the quality factor, both are essentially the same.

[0057] Based on the above formula 1, the spectral ratio method is the most
commonly used method for estimating a quality factor, and this method
estimates the quality factor by utilizing a linear relation between the
spectrum ratio logarithm and the frequency of seismic wavelets at two
different times. However, the spectrum ratio logarithm is easily affected
by amplitude spectrum frequency notch and noise, which results in an
oscillation that occurs on a linear relation between it and the
frequency, thereby affecting the stability of estimating the quality
factor. Therefore, an index method was previously proposed, which obtains
an interlayer quality factor using a forward matching approach by solving
the minimal value of the following equation:

[0058] Where f1 and f2 represent a lower frequency limit and an
upper frequency limit, respectively, and in order to eliminate the
indeterminate Ck in the above formula 2, a derivation approach can
be used such that ∂G/∂Ck=0, thereby
obtaining:

[0059] Formula 3 is substituted into formula 2, then the formula 2 merely
contains one indeterminate coefficient, such that Qk , which allows
the formula 2 to have the minimum value, can be obtained by way of
scanning the quality factor.

[0060] In order to verify the performance of the quality factor estimation
method, a forward modeling approach can be used to obtain attenuation VSP
records as shown in FIG. 4, in order to eliminate the effects of other
factors as much as possible, a first-arrival wave field of a down-going
direct wave is only simulated in FIG. 4, and a change in wavelet waveform
at adjacent channels is only caused by the interlayer quality factor.

[0061] With respect to forward modeling records as shown in FIG. 4, weak
random noise (wherein noise energy accounts for 0.3% of effective signal
energy) is introduced, an estimation of the quality factor of noise-free
data and noise data is performed by the index method, respectively. The
estimated results are as shown in FIGS. 5 and 6. As can be seen from the
estimated results, when noise is not contained in the data, the quality
factor estimation results coincide quite well with the theoretical values
(as shown in FIG. 5), when noise is contained, there is a deviation
between the quality factor estimation results and theoretically true
values (as shown in FIG. 6), wherein in FIGS. 5 and 6, the solid line
represents a theoretical value, and the dotted line represents the
quality factor estimation results.

[0062] As can be seen from FIG. 6, the quality factor estimation result of
noise data between 9th and 10th channel in FIG. 4 is 206, and
relative to the true value 150, the absolute error of the estimation
result is 56 and the relative error is 37.3%.

[0063] In order to analyze the causes of the error of the index method, a
scanning range of the quality factor is set as 1 to 300, Ck in
coefficient formula 3 and matching errors in formula 2 are calculated,
respectively. In the absence of noise, the quality factor corresponding
to the minimum matching error is 150 as shown in FIG. 7, in this case,
the coefficient Ck corresponding to the quality factor is 1 as shown
in FIG. 8, which is fully consistent with the true value. However, in the
case of noise, the quality factor corresponding to the minimum matching
error is 206 as shown in FIG. 9, in this case, the coefficient Ck
corresponding to the quality factor is 0.9948 as shown in FIG. 10, which
are both deviated from the true value.

[0064] In order to further observe its stability, a scanning range of
Qk is set as 1 to 300, and a scanning range of the coefficient
Ck is set as 0.8 to 1.35, matching error distribution diagrams of
the noise-free data and the noise data are obtained, respectively, and it
is obtained by analyzing that in the vicinity of the true value (i.e.,
Qk=150, Ck=1), the matching error is located in the bottom, and
the trend is very gentle, and this causes that if there exists a little
noise in the original data, the minimum matching error (0.05595) may
deviate from the true minimum matching error (0.0007557), thereby causing
the estimation result of the quality factor (Qk=206) to deviate from
the true value. In the case of noise, Ck becomes 0.9948, and for the
forward record as shown in FIG. 4, the actual theoretical value should be
1, and thus, the indeterminate coefficient Ck in the above formula 3
is one reason that makes the method unstable, and for the noise data, if
Ck is set to 1, the results after calculating the quality factor by
re-utilizing the index method are shown in FIG. 11, it can be found that
the goodness of fit between the quality factor estimation result and the
theoretical value is significantly improved.

[0065] Also, for data between 9th and 10th channel in FIG. 4, a
stability analysis is conducted for the index method on the premise that
the coefficient Ck is a known theoretical value. For the noise-free
data and the noise data, a scanning range of the quality factor is set as
1 to 300, the corresponding matching errors are calculated, as shown in
FIGS. 12 and 13. It can be seen that the minimum value is obviously
located at a trough in the curve, as compared with FIGS. 7 and 9, in the
case of noise effects, in FIG. 13, the quality factor estimation result
changes from 150 to 155, and the stability is significantly improved.

[0066] Thus, based on the above analysis, if the coefficient Ck can
be obtained, and then the accuracy of estimating the quality factor by
the formula 2 can be further improved, and it is analyzed below how to
obtain the coefficient Ck.

[0067] For first arrival of direct wave of the zero offset VSP data at
adjacent channels, the coefficient Ck thereof generally includes two
aspects: a geometric diffusion effect Gk during propagation and
transmission loss Pk at a wave impedance interface. In which, an
amplitude attenuation caused by the geometric diffusion effect can be
compensated through a geometric diffusion correction, thus the problem of
obtaining the coefficient Ck is converted into how to solve the
transmission loss Pk caused by the wave impedance interface. For
zero offset VSP data, in accordance with an arrival time of each channel
direct wave and a depth of the detection points, an average velocity from
the surface to the detection points can be obtained, and then it is
converted into an interval velocity, such that a transmission coefficient
between two adjacent channels can be obtained, that is,

[0069] The above formula 5 is an objective function of the improved index
method, the Q value corresponding to the minimum matching error obtained
by way of Q scanning serves as an obtained interlayer quality factor.

[0070] In order to test the feasibility of the method, the velocity model
and the quality factor model as shown in FIG. 14 are given, the seismic
source is located at the surface, the depth of the receiving points is
100-800 m, and an interval of the receiving points is 10 m; and a zero
offset VSP full wave field, a down-going wave field and an up-going wave
field are obtained, respectively, by using the propagation matrix method
including absorption attenuation effect for performing forward numerical
simulation.

[0071] For the down-going wave field, random noise (wherein energy of
noise accounts for 0.3 of the effective signal energy) is introduced, and
the quality factors for the noise-free data and the noise data are
calculated, respectively. It is found from the estimated results of the
quality factors that for the noise-free data, as shown in FIG. 15, the
estimation results of the spectrum ratio method, the index method and the
estimation method in the present embodiment all coincide quite well with
the true values. For the noise data, when the quality factor is
relatively small (for example, 20 and 40), the estimation results of the
three methods all coincide quite well with the true values, however, when
the quality factor is relatively large (for example, 80 and 120), there
exists estimation offsets to some extent in the three methods, the
spectral ratio method, as shown in FIG. 16, has a large offset,
especially when the quality factor is 120, the estimation result is
difficult to be accepted; as to the index method, as shown in FIG. 17,
the estimation result is highly improved relative to the spectrum ratio
method; and the estimation method in the present embodiment, as shown in
FIG. 18, further improves the estimation results of the quality factor.
In the above-described FIG. 15 to FIG. 18, bold lines represent the true
values and thin lines represent the estimation results.

[0072] The stability and accuracy of estimating the quality factor can be
effectively improved by the aforementioned manner in which the quality
factor is estimated.

[0073] In another embodiment, a software for performing the technical
solutions described in the above embodiments and preferred embodiments
are further provided. p In another embodiment, it is further provided a
storage medium in which the above software is stored, and the storage
medium includes but not limited to a compact disc, a floppy disk, a hard
disk, an erasable memory and the like.

[0074] As can be seen from the above descriptions, the embodiments of the
present invention achieve the following technical effects: a transmission
coefficient between two VSP channels is determined through an interval
velocity of a seismic wave, and then the transmission coefficient is
determined as an indeterminate coefficient in an objective function of
the index method, and the quality factor is estimated according to the
objective function of the index method, thereby solving the technical
problem of lower stability and accuracy of estimating the quality factor
due to the existence of the indeterminate coefficient in the process of
estimating the quality factor by adopting the index method in the prior
art, and achieving the technical effect of improving stability and
accuracy of estimating the quality factor.

[0075] Obviously, the persons skilled in the art should appreciate that
the respective modules or steps in the abovementioned embodiments of the
present invention can be implemented by using a general computing device,
they can be focused on a single computing device or distributed on a
network consisting of multiple computing devices, and alternatively, they
can be implemented using a program code executable by a computing device,
thus they can be stored in the storage device to be executed by the
computing device, and, in some cases, the steps as illustrated or
described may be executed in an order different from that described
herein, or they can be fabricated as various integrated circuit module,
respectively, or a plurality of modules or steps therein are fabricated
as a single integrated circuit module. Thus, the embodiments of the
present invention are not limited to any specific combination of hardware
and software.

[0076] The above are just preferred embodiments of the present invention,
and are not intended to limit the present invention. For persons skilled
in the art, various modifications and changes can be made to the
embodiments of the present invention. Any modification, equivalent
replacement and improvement made within the spirit and principle of the
present invention shall be covered in the protection scope of the present
invention.